Software Engineer (Architecture)

• Advance the state of the art in compiler and runtime technology for delivering high-performance acceleration of AI workloads across a variety of neural network architectures.
• Research and design new software and hardware AI solutions, involving simulators, optimizing compilers, code generators, and runtime execution frameworks for deep learning accelerators.
• Evaluate various trade-offs of different parallelization strategies such as performance, power, energy, and memory consumption.
• Enhance AI software tools to support the latest and greatest DNNs emerging from the research community and industry.
• Keep up with the fast-paced development happening in the industry and academia to continuously enhance our products.
• Work closely with other software and hardware engineers to develop the next generation of deep learning software.
• Collaborate with architects and hardware engineers to co-design future accelerators.

• 10+ years of experience developing software for a variety of highly parallel architectures.
• Previous roles include experience with optimizing algorithms for hardware acceleration machine learning accelerators, spatial architectures, or GPUs.
• Strong problem-solving skills and the ability to resolve complex issues with a high level of ambiguity.
• Understanding of Deep Learning fundamentals.
• Strong development skills in C/C++, Python.
• Superb soft skills: ability to work efficiently and effectively in a group environment, and influence a cross-functional team without having direct managerial authority.
• Computer Science, Engineering, or related degree; preferably MS or PhD.
• Driven and self-directed.

Our client is a company building the world’s highest- performance pure digital AI inference chip.